R: Continuous Wavelet Transform with derivative of Gaussian

DOG {Rwave} | R Documentation

## Continuous Wavelet Transform with derivative of Gaussian

### Description

Computes the continuous wavelet transform with for (complex-valued) derivative of Gaussian wavelets.

### Usage

    DOG(input, noctave, nvoice=1, moments, twoD=TRUE, plot=TRUE)

### Arguments

`input` | input signal (possibly complex-valued).
`noctave` | number of powers of 2 for the scale variable.
`moments` | number of vanishing moments of the wavelet (order of the derivative).
`nvoice` | number of scales in each octave (i.e. between two consecutive powers of 2)
`twoD` | logical variable set to T to organize the output as a 2D array (signal\_size x nb\_scales), otherwise, the output is a 3D array (signal\_size x noctave x nvoice)
`plot` | if set to T, display the modulus of the continuous wavelet transform on the graphic device

### Details

The output contains the (complex) values of the wavelet transform of the input signal. The format of the output can be

2D array (signal\_size x nb\_scales)

3D array (signal\_size x noctave x nvoice)

### Value

continuous (complex) wavelet transform

### References

See discussions in the text of “Practical Time-Frequency Analysis”.

### See Also

`cwt`, `cwtp`, `cwtsquiz`, `cgt`.

### Examples

     x <- 1:512
        chirp <- sin(2*pi * (x + 0.002 * (x-256)^2 ) / 16)

     DOG(chirp, noctave=5, nvoice=12, 3, twoD=TRUE, plot=TRUE)

[Package Rwave version 2.4-8 Index]